Over the past year, data breaches, through web, business, and mobile application exploitation, have continued to run rampant. In 2018, major household names like Ticketmaster, the United States Postal Service (USPS), Air Canada, and British Airways were hit by application-based exploits.

WhiteHat is positioned extremely well to capitalize on recent developments in ML. ML allows us to make sense of the data, train a set of expert networks on this data, and then use these networks to supplement our human element.

Learn what constitutes an ideal static analysis (SAST) solution, the importance of depth of coverage, and some causes of false positives – how they come up, why they happen, and what can be done about them.

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